Trajectory Raises $45 Million to Make AI Model Training Accessible to Nontechnical Experts
AI models generally do not learn from mistakes unless they are trained again. Companies adapting general-purpose models for fields such as law and finance often rely on specialist research teams or costly consultants to fine-tune them.
Trajectory, founded about a year ago by three Stanford classmates with backgrounds at Google DeepMind and Apple, is seeking to automate that work. The 18-person startup has raised $45 million in a Series A led by Sequoia, with participation from Nvidia, Bessemer Venture Partners, and Bain Capital Ventures. The round values the company at $300 million.
Trajectory’s platform lets businesses connect an open-source AI model to their applications and collect feedback on its performance. The company uses that feedback to retrain the model so it can improve at specialized tasks over time. Co-founder Ronak Malde said the goal is to help models gain the job-specific experience that foundational models lack.
Companies including Harvey and Rogo use Trajectory to post-train open-source models for tasks such as reviewing particular types of legal contracts or valuing companies according to specific methodologies. Decagon, Mercor, and Nvidia are also customers. Trajectory is now making its post-training platform publicly available.
The startup says its approach keeps people involved in deciding what successful performance looks like. That distinguishes it from fully autonomous self-improvement, which co-founder Michael Elabd says could produce unintended or dangerous results.
Trajectory faces competition from Thinking Machines Lab, Applied Compute, and Prime Intellect. Malde points to the team as a key advantage: he previously worked at Google DeepMind and was among researchers hired from Windsurf, while Elabd also worked at DeepMind and co-founder Arjun Karanam worked on generative foundation models at Apple. The company has also recruited talent from OpenAI, Stripe, and Netflix.
Karanam said the company’s interface is designed to make post-training accessible to customers without technical expertise.
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